Semantic Fingerprinting and Machine Learning for Content Discovery

Molecular Connections worked with a physical sciences publishing society (AIPP) on content discoverability: building a rich ontology and semantically enriching millions of backfile articles using semantic fingerprinting and content classification.

Benefits & outcomes

1,500,000 candidate terms distilled to 35,000 across 26,000 topics; a million articles semantically indexed.

Real-time indexing of new articles.

Expanded reviewer database drawn from authors, editors and referees.

Thesaurus-driven contextual ad space as a side effect.

Delivered in under six months.

Notes & quotes

"The MC team ensured the ontology built was a manifestation of AIPP’s content."

"The solution provided polyhierarchical support and semantically indexed 1 million articles with high accuracy."


Publisher / company: Molecular Connections
Date of mention: 01/01/2025
Source: https://mcpublishing.co.in/case_studies/improving-content-discovery-using-semantic-fingerprinting-and-machine-learning/